This invention relates to translation systems for translating a source language, e.g., natural language, into a target language, e.g., artificial language, and more particularly, the invention relates to such translation systems employing statistical methods.
It is known that statistical translation models were first introduced by P. F. Brown et al. in the article entitled: "The Mathematics of Statistical Machine Translation; Parameter Estimation," Computational Linguistics, 19(2), pp. 263-311 (June 1993). Such models were created in the context of French to English translation and were based on a source-channel paradigm. The source-channel paradigm uses two component models. The first model is known as the channel model and is defined as the probability of occurrence of a source language sentence S given a target language sentence T, that is, the conditional probability of the occurrence of S, given T, i.e., P(S.vertline.T). The second model is known as the language (or source) model and is defined as the probability of occurrence of T, i.e., P(T). The two component models are then used to compute the probability of the occurrence of T, given S, i.e., P(T.vertline.S), via the relationship P(T.vertline.S)=P(S.vertline.T).multidot.P(T)/P(S). The target language sentence T which maximizes the product P(S.vertline.T).multidot.P(T) is chosen as the translation of the input source language sentence S. The channel model can also be thought of as a translation model, but, with the translation being performed from target to source. Each of the component models are estimated independently.
It is also known that such a priori models, as described above, may be used in the context of natural language translation as disclosed in U.S. Pat. No. 5,510,981 to Berger et al. issued on Apr. 23, 1996, and more recently for understanding in both the paper by M. Epstein entitled "Statistical Source Channel Models for Natural Language Understanding," Ph. D. Thesis, New York University (September 1996) and in a related patent application identified by U.S. Ser. No. 08/593,032.
However, given a source sentence S, for example, in a natural language such as English, it would be advantageous to be able to translate such sentence into a target language sentence T, for example, in an artificial (formal) language such as a database query language, utilizing a translation system employing a single statistical translation model. It would further be advantageous if said system were generally data-driven, built automatically from training data, and did not use domain-specific rules developed by experts so that it could be easily ported to new domains.